Engineering construction scaffold intelligent safety management system and method thereof
An intelligent system that combines video surveillance and image analysis with data analysis solves the problems of slow inspections, poor data, and high costs in scaffolding safety management, achieves real-time risk identification and automatic cleaning, reduces operation and maintenance costs, and improves construction safety and economy.
Patent Information
- Application Number
- CN202510800117.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-16
- Publication Date
- 2025-09-19
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
In the existing technology, scaffolding safety management relies on manual inspections and single parameter monitoring, which has problems such as long inspection cycles, low data accuracy, high costs and poor environmental adaptability, making it difficult to achieve real-time and accuracy requirements.
Using video surveillance modules, image parsing modules, data analysis modules, notification modules and safety enclosure execution modules, combined with infrared cameras, automatic flushing systems and support reinforcement structures, real-time monitoring and automatic cleaning of scaffolding can be achieved, and environmental variables can be integrated for risk assessment and reinforcement.
The real-time performance and data accuracy of scaffolding safety management have been improved, operation and maintenance costs have been reduced, and construction safety and economic benefits have been ensured.
Smart Images
Figure CN120673011A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of engineering safety management, in particular to an intelligent safety management system for engineering construction scaffolding and a method thereof. Background Art
[0002] In the construction industry, scaffolding, as the fundamental support infrastructure for aerial work, is crucial for worker safety and project progress. As construction projects grow in scale and complexity, traditional safety management models based on manual inspections and single-parameter monitoring are no longer able to meet real-time and accurate safety requirements. Intelligent management systems are urgently needed to achieve full-cycle risk control.
[0003] Existing technology primarily relies on regular manual inspections and single-point monitoring with mechanical sensors, presenting significant technical bottlenecks. First, manual inspections are long (averaging four hours), making it difficult to promptly detect hidden dangers such as structural deformation and overload, and are subject to significant subjective judgment. Second, traditional monitoring equipment lacks automatic cleaning mechanisms, leading to high PM2.5 adhesion rates on monitoring heads caused by construction dust, resulting in data accuracy often below 60%. Furthermore, these systems fail to incorporate environmental variables such as temperature and wind speed, making them susceptible to failure in extreme temperatures between -20°C and 40°C or typhoon-level winds. Furthermore, manual cleaning and emergency reinforcement are costly, with overall operation and maintenance costs exceeding 60% compared to intelligent solutions, making it difficult to strike a balance between safety and affordability. Summary of the Invention
[0004] In view of the shortcomings of the existing technology, the present invention provides an intelligent safety management system and method for engineering construction scaffolding, which solves the problems of slow inspection, poor data, high cost and weak environmental adaptability in scaffolding safety management during engineering construction.
[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent safety management system for engineering construction scaffolding, characterized by including a video monitoring module, an image parsing module, a data analysis module, a notification module, a visualization module and a safety enclosure execution module: The video monitoring module includes an infrared camera unit and a video storage unit, the infrared camera unit is used to perform infrared photography on the scaffolding, and the video storage unit is used to classify and store infrared image data sets; The image analysis module includes a target detection unit, a feature extraction unit and an image analysis unit. The target detection unit is used to identify scaffolding, personnel and materials. The feature extraction unit is used to obtain features such as tilt angle and load volume. The image analysis unit is used to organize data sets. The data analysis module includes a data cleaning and preprocessing unit and a data modeling unit. The data cleaning and preprocessing unit is used for data standardization. The data modeling unit calculates the load value through a formula. , inclination , deformation coefficient : in, is the real-time temperature, is the real-time wind speed; The notification module includes a notification generating unit and a notification transmitting unit. The notification generating unit generates notifications based on the risk factors. Generate a level policy, and notify the delivery unit to send notifications via SMS, alarms, etc.; The visualization module is used to display data such as load factors and risk factors in charts; The safety enclosure execution module includes an automatic flushing system and a support reinforcement structure. The automatic flushing system flushes the monitoring head through a collection bucket and a leakage tray. The support reinforcement structure includes an adjustable support foot and a reinforcement plate.
[0006] Preferably, the data analysis module is also used to calculate the load factor : in, .
[0007] Preferably, the load factor Compare with the threshold to generate a ranking strategy: It is the first level load evaluation and no intervention is required; It is rated as level five load and the use of scaffolding is prohibited.
[0008] Preferably, in the automatic flushing system of the safety enclosure execution module, the first leakage hole at the bottom of the collection bucket is adapted to the blocking rod, and the leakage plate slides through the guide rod. When the amount of rainwater in the collection bucket reaches a threshold, the blocking rod is flushed open, and the water body flushes the monitoring head through the second leakage hole.
[0009] Preferably, the data analysis module is also used to calculate the tilt coefficient : in, .
[0010] Preferably, the risk factor Through the stability factor and deformation coefficient Fitting: Among them, when When the scaffolding is removed, a five-level hazard assessment is generated and a notice is given to remove the scaffolding.
[0011] Preferably, in the support and reinforcement structure of the safety enclosure execution module, the support base is provided with an assembly opening, the reinforcement plate is plugged into the assembly opening through a toothed groove, and the positioning frame cooperates with the positioning opening to limit the position.
[0012] Preferably, the infrared camera unit of the video surveillance module supports 24-hour real-time monitoring, and the video storage unit adopts H.265 encoding compression, saving more than 50% of storage space.
[0013] Preferably, the method comprises the following steps: Step 1: Obtain infrared images of the scaffolding through the video monitoring module; Step 2: The image analysis module extracts features such as tilt angle and load value; Step 3: Data analysis module calculates risk factors ; Step 4: The notification module sends a strategy based on the risk level; Step 5: The visualization module displays risk data.
[0014] Preferably, the risk factor calculation in step three is combined with the monitoring head contamination degree parameter of the safety enclosure execution module, and the contamination degree is associated with the flushing frequency. When the contamination index is greater than 70, the flushing system is automatically triggered.
[0015] The present invention provides an intelligent safety management system and method for engineering construction scaffolding, which has the following beneficial effects: 1. This invention uses the infrared camera unit of the video monitoring module to capture scaffolding infrared images in real time 24 hours a day. Combined with the image analysis module's extraction of features such as tilt angle and load volume, and then through the multi-formula calculations of the data analysis module, it achieves comprehensive monitoring of the scaffolding's status. When a risk factor exceeds a preset threshold, the notification module promptly transmits a tiered policy through various means, reducing risk identification delays from an average of four hours for traditional manual inspections to within 15 minutes, significantly improving incident response efficiency and ensuring construction safety.
[0016] 2. This invention utilizes the automatic flushing system of the safety enclosure execution module to collect rainwater in a collection hopper. When the rainwater volume reaches a threshold, the blocking rod is flushed open, and the water flushes the monitoring head through the second leak hole in the leakage tray. This design achieves a 92% cleaning efficiency against PM2.5, a 37% improvement over traditional rainwater flushing. This effectively eliminates the problem of monitoring head contamination caused by construction dust, ensures monitoring data accuracy of ≥98%, and provides reliable data support for scaffolding safety management.
[0017] 3. By incorporating real-time environmental variables such as temperature and wind speed into the calculation formula of the data analysis module, this invention enables the system to operate stably in temperatures between -20°C and 40°C and at typhoon-level wind speeds, breaking through the environmental limitations of traditional systems. Furthermore, the automatic flushing system utilizes rainwater resources, reducing costs by 85% compared to manual cleaning. The multi-parameter analysis module reduces scaffolding reinforcement costs by 30% by providing early warning of potential risks, and overall operation and maintenance costs by 60% compared to traditional solutions, achieving dual optimization of safety performance and economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] Figure 1 is a flow chart of the present invention; Figure 2 It is a system diagram of the present invention. DETAILED DESCRIPTION
[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.
[0020] Example 1: Please see the attached Figure 1 and attached Figure 2 The embodiment of the present invention provides an intelligent safety management system for engineering construction scaffolding, including a video monitoring module, an image parsing module, a data analysis module, a notification module, a visualization module and a safety enclosure execution module: The video surveillance module includes an infrared camera unit and a video storage unit. The infrared camera unit is used to take infrared photos of the scaffolding, and the video storage unit is used to classify and store infrared image data sets. The infrared camera unit of the video surveillance module supports 24-hour real-time monitoring, and the video storage unit adopts H.265 encoding compression, saving more than 50% of storage space; the image parsing module includes a target detection unit, a feature extraction unit and an image parsing unit. The target detection unit is used to identify scaffolding, personnel and materials, the feature extraction unit is used to obtain features such as tilt angle and load volume, and the image parsing unit is used to organize data sets; the data analysis module includes a data cleaning and preprocessing unit and a data modeling unit. The data cleaning and preprocessing unit is used for data standardization, and the data modeling unit calculates the load value through a formula , inclination , deformation coefficient : in, is the real-time temperature, The data analysis module is also used to calculate the load factor for real-time wind speed. : in, , load factor Compare with the threshold to generate a ranking strategy: It is the first level load evaluation and no intervention is required; The load rating is level 5 and scaffolding is prohibited. The data analysis module is also used to calculate the inclination coefficient. : in, ; The notification module includes a notification generating unit and a notification transmitting unit, the notification generating unit Generate a level strategy, and the notification delivery unit sends notifications through SMS, alarms, etc. The visualization module is used to display data such as load factor and risk factor in charts. Through the stability factor and deformation coefficient Fitting: Among them, when When the level 5 hazard assessment is generated, the scaffolding will be notified to be removed; the safety enclosure execution module includes an automatic flushing system and a support reinforcement structure. The automatic flushing system flushes the monitoring head through the collection bucket and the leakage tray. The support reinforcement structure includes an adjustable support foot and a reinforcement plate. In the automatic flushing system of the safety enclosure execution module, the first leakage hole at the bottom of the collection bucket is adapted to the blocking rod, and the leakage tray slides through the guide rod. When the amount of rainwater in the collection bucket reaches the threshold, the blocking rod is flushed open, and the water body flushes the monitoring head through the second leakage hole. In the support reinforcement structure of the safety enclosure execution module, an assembly port is opened in the support base, the reinforcement plate is plugged into the assembly port through a toothed groove, and the positioning frame cooperates with the positioning port to limit the position.
[0021] An intelligent safety management method for engineering construction scaffolding includes the following steps: Step 1: Obtain infrared images of the scaffolding through the video monitoring module; Step 2: The image analysis module extracts features such as tilt angle and load value; Step 3: Data analysis module calculates risk factors ,The hazard factor calculation in step 3 is combined with the monitoring head contamination degree parameter of the safety enclosure execution module. The contamination degree is associated with the flushing frequency. When the contamination index is greater than 70, the flushing system is automatically triggered; Step 4: The notification module sends a strategy based on the risk level; Step 5: The visualization module displays risk data.
[0022] Example 2: 1. Scene Background During a bridge construction project in a coastal area, a typhoon warning (wind speed ≥ 12m / s) and heavy rain were issued, forcing the scaffolding to withstand strong wind loads and rain erosion. The system activated its extreme environment response mechanism, with the following specific implementation steps: S1. Video surveillance and data collection enhancement The infrared camera unit switches to anti-light interference mode, with a resolution increased to 4K, capturing the scaffold's minute vibrations in strong winds in real time (with an accuracy of 0.1mm). An anti-shake algorithm is used to reduce image blur. The video storage unit uses incremental storage mode to record only dynamically changing images. Combined with H.265 encoding, it can continuously store 72 hours of data during heavy rain, saving 60% of storage space. S2. Image parsing and feature extraction optimization Target Detection Unit: Focuses on identifying signs of loosening of scaffolding node connectors (such as fasteners) through infrared thermal imaging temperature difference analysis (temperature difference > 5°C is marked as a potential hidden danger), with an identification rate of 95%; Feature extraction unit: Real-time calculation of the tilt angle (Qx) under typhoon load: Using binocular vision ranging, the measured tilt angle of a certain pole is Qx = 2.8° (exceeding the preset threshold of 2°), and the load value Fz = 1200kg (close to the rated load of 1500kg); S3. Data analysis and risk warning upgrade Data cleaning unit: removes infrared image noise caused by heavy rain and smoothes the tilt data using the Kalman filter algorithm with an error rate of ≤0.5%; Data Modeling Unit: Calculate key parameters: Deformation coefficient : (Real-time temperature α=25°C, wind speed β=12m / s, surface object moving speed Yd=1.2m / s); Load factor : (Preset load value Yszz = 1500kg, service life δ = 1 year, material cz = 0.7, material type cl = 0.6, distribution density fb = 0.5, weight coefficients a1+a2 = 1.5, a3+a4+a5 = 1.5), corresponding to the third level load evaluation, emergency unloading is required; Risk factors : The inclination coefficient Qxxs = 18.5, the correction constant ω = 1.3), the fitting result is Wxyz = 31.2, triggering the third-level hazard assessment (40≤Wxyz≤59), and the system automatically generates the "strong wind reinforcement + partial unloading" strategy; S4. Strengthening notification and response mechanisms Notification generation unit: Generates notifications containing a 3D risk map, noting weak points in the scaffolding (e.g., the inclination of the southwest corner pole exceeds the standard), with the content: "Typhoon warning: Scaffolding load and inclination exceed the limit, requiring immediate reinforcement of the southwest support." Notification delivery unit: Sends notifications via Beidou satellite SMS (in case of base station signal interruption), site alarm (sound pressure level ≥ 85dB), and helmet built-in vibrator, with a response time of ≤ 10 minutes. S5, Visualization and Intelligent Execution Linkage Visualization module: Displays typhoon simulation animation on the monitoring screen, superimposed with scaffolding stress cloud map. Red areas indicate stress exceeding 80% of yield strength, guiding construction workers to accurately reinforce. Safety enclosure execution module: Automatic flushing system: Automatically shuts down the flushing function during heavy rain to prevent excessive water accumulation from increasing the load, and simultaneously activates the collection bucket drain valve to avoid rainwater accumulation. Support reinforcement structure: The adjustable support foot automatically rises 3cm to compensate for the tilt caused by foundation settlement. The hydraulically driven reinforcement plate is inserted into the assembly port, and the bearing capacity is increased by 40% after the toothed groove is engaged. The locking error between the positioning frame and the positioning port is ≤0.2mm.
[0023] 2. Methods and Steps Adapted to Extreme Environments Data fusion optimization: The risk factor calculation in step three incorporates typhoon wind speed forecast data (wind speed ≥ 15m / s for the next three hours), triggering reinforcement strategies in advance, two hours earlier than traditional manual response. Pollution-flush logic adjustment: When the pollution index naturally clears due to heavy rain, the system suspends automatic flushing, saving 80% of water resources and preventing misjudgments from monitoring heads due to slippery conditions. Energy consumption management: Non-critical modules (such as infrared supplemental lighting at night) automatically operate at reduced power, reducing overall system energy consumption by 30% during typhoons and ensuring 72 hours of continuous backup power.
[0024] 3. Implementation Effect Verification Risk Control Capabilities: During a 48-hour typhoon (maximum wind speed of 14 m / s), the scaffolding tilt was kept within 3.5° (traditional solutions could exceed 5°), and no component fallout occurred. Data Accuracy: Through Kalman filtering and multi-sensor fusion, the accuracy of key data such as tilt and load values remained at 97%, a 40% improvement over manual inspections. Cost-Effectiveness: The automated reinforcement strategy reduced labor by six man-hours, avoiding approximately 200,000 yuan in losses from typhoon-related work stoppages and reducing overall O&M costs by 65% compared to traditional solutions.
[0025] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.
Claims
1. An intelligent safety management system for engineering construction scaffolding, characterized in that: It includes video surveillance module, image parsing module, data analysis module, notification module, visualization module and safety enclosure execution module: The video monitoring module includes an infrared camera unit and a video storage unit, the infrared camera unit is used to perform infrared photography on the scaffolding, and the video storage unit is used to classify and store infrared image data sets; The image analysis module includes a target detection unit, a feature extraction unit and an image analysis unit. The target detection unit is used to identify scaffolding, personnel and materials. The feature extraction unit is used to obtain features such as tilt angle and load volume. The image analysis unit is used to organize data sets. The data analysis module includes a data cleaning and preprocessing unit and a data modeling unit. The data cleaning and preprocessing unit is used for data standardization. The data modeling unit calculates the load value through a formula. , inclination , deformation coefficient : in, is the real-time temperature, is the real-time wind speed; The notification module includes a notification generating unit and a notification transmitting unit. The notification generating unit generates notifications based on the risk factors. Generate a level policy, and notify the delivery unit to send notifications via SMS, alarms, etc.; The visualization module is used to display data such as load factors and risk factors in charts; The safety enclosure execution module includes an automatic flushing system and a support reinforcement structure. The automatic flushing system flushes the monitoring head through a collection bucket and a leakage tray. The support reinforcement structure includes an adjustable support foot and a reinforcement plate.
2. The intelligent safety management system for engineering construction scaffolding according to claim 1 is characterized in that: The data analysis module is also used to calculate the load factor : in, .
3. The intelligent safety management system for engineering construction scaffolding according to claim 2 is characterized in that: The load factor Compare with the threshold to generate a ranking strategy: When it is the first level load evaluation, no intervention is required; It is rated as level five load and the use of scaffolding is prohibited.
4. The intelligent safety management system for engineering construction scaffolding according to claim 1 is characterized in that: In the automatic flushing system of the safety enclosure execution module, the first leakage hole at the bottom of the collection bucket is adapted to the blocking rod, and the leakage plate slides through the guide rod. When the amount of rainwater in the collection bucket reaches a threshold, the blocking rod is flushed open, and the water body flushes the monitoring head through the second leakage hole.
5. The intelligent safety management system for engineering construction scaffolding according to claim 1 is characterized in that: The data analysis module is also used to calculate the tilt coefficient : in, .
6. The intelligent safety management system for engineering construction scaffolding according to claim 1 is characterized in that: The risk factors Through the stability factor and deformation coefficient Fitting: Among them, when When the scaffolding is removed, a five-level hazard assessment is generated and a notice is given to remove the scaffolding.
7. The intelligent safety management system for engineering construction scaffolding according to claim 1 is characterized in that: In the support and reinforcement structure of the safety enclosure execution module, the support base is provided with an assembly opening, the reinforcement plate is plugged into the assembly opening through a toothed groove, and the positioning frame cooperates with the positioning opening to limit the position.
8. The intelligent safety management system for engineering construction scaffolding according to claim 1 is characterized in that: The infrared camera unit of the video surveillance module supports 24-hour real-time monitoring, and the video storage unit adopts H.265 encoding compression, saving more than 50% of storage space.
9. An intelligent safety management method for engineering construction scaffolding, using an intelligent safety management system for engineering construction scaffolding according to any one of claims 1 to 8, characterized in that: The following steps are involved: Step 1: Obtain infrared images of the scaffolding through the video monitoring module; Step 2: The image analysis module extracts features such as tilt angle and load value; Step 3: Data analysis module calculates risk factors ; Step 4: The notification module sends a strategy based on the risk level; Step 5: The visualization module displays risk data.
10. The intelligent safety management method for engineering construction scaffolding according to claim 9, characterized in that: The risk factor calculation in step three is combined with the monitoring head contamination degree parameter of the safety enclosure execution module. The contamination degree is associated with the flushing frequency. When the contamination index is greater than 70, the flushing system is automatically triggered.